Methods and systems for intraoperatively confirming location of tissue structures

ABSTRACT

Systems, methods and devices are provided for intraoperatively confirming location of tissue structures during medical procedures. Preoperative image data of a patient&#39;s skeletal structure in a vicinity of an anatomical part undergoing a medical procedure is acquired. During the procedure, after exposing tissue intraoperative image data is acquired by scanning a selected region of tissue, in a vicinity of the skeletal structure using Polarization Sensitive-Optical Coherence Tomography (PS-OCT). Regions of tissue exhibiting structural organization in the vicinity of the skeletal structure are identified from the intraoperative (PS-OCT) image data. Geometrically correlating and registering the intraoperative (PS-OCT) image data with the preoperative image data of the skeletal structure in the vicinity of the anatomical part is then performed using a priori known anatomical information about the regions of tissue exhibiting structural information.

PRIORITY CLAIMS

This application claims priority to International Patent Application No.PCT/CA2014/050268, titled “SURGICAL IMAGING SYSTEM” and filed on Mar.14, 2014, the entire contents of which is incorporated herein byreference for the purposes of any U.S. national phase application orcontinuation-by-pass application filed from, and claiming priority, fromthis International PCT patent application.

FIELD

The present disclosure relates to imaging methods for use in minimallyinvasive therapy and image guided medical procedures using opticalimaging, and more particularly, hyperspectral imaging.

BACKGROUND

The optical absorption and scattering properties of biological tissuedepend on both the chemical and structural properties of the tissue andthe wavelength of the interacting light. How these absorption andscattering properties of tissue change as a function of light can beparticularly useful, as it is often unique to chemicals or structures inthe tissue (the spectrum of the tissue). For example the absorptionfeatures of oxy- and deoxy-hemoglobin can be used to measure theoxygenation of blood and tissue, and the scatter changes caused bydifference cellular sizes can be used to detect precancerous andcancerous tissue. The field of measuring these changes in opticalproperties, as a function of light, is known as spectroscopy and thedevice to measure the light at the various wavelengths is known as aspectrometer. Spectroscopy has found a wealth of current and potentialapplications in medicine.

Traditional spectrometers measure the spectrum of light from a singlepoint of a sample. However, the spectrum from multiple spatial pointscan be combined to form a 3D spatial dataset (sometimes referred to as ahypercube), where the first two dimensions are spatial and the third iswavelength. In other words, each image pixel has an entire spectrumrather than just an intensity or RBG value. This is known ashyperspectral imaging and is a powerful technique as spatially resolvedtissue chemical or microstructural properties can imaged, thus providinga more complete understanding of the tissue and may be a usefultechnique for tissue differentiation. According to a paper by Dicker etal [Differentiation of Normal Skin and Melanoma using High ResolutionHyperspectral Imaging], hyperspectral image analysis (or hyperspectralimaging) was applied to search for spectral differences between benignand malignant dermal tissue in routine hematoxylin eosin stainedspecimens (i.e., normal and abnormal skin, benign nevi and melanomas).The results revealed that all skin conditions in the initial data setscould be objectively differentiated providing that staining and sectionthickness was controlled.

SUMMARY

Systems, methods and devices are provided for intraoperativelyconfirming location of tissue structures during medical procedures.

In an embodiment, preoperative image data of a patient's skeletalstructure in a vicinity of an anatomical part undergoing a medicalprocedure is acquired. During the procedure, after exposing tissueintraoperative image data is acquired by scanning a selected region oftissue, in a vicinity of the skeletal structure using PolarizationSensitive-Optical Coherence Tomography (PS-OCT). Regions of tissueexhibiting structural organization in the vicinity of the skeletalstructure are identified from the intraoperative (PS-OCT) image data.Geometrically correlating and registering the intraoperative (PS-OCT)image data with the preoperative image data of the skeletal structure inthe vicinity of the anatomical part is then performed using a prioriknown anatomical information about the regions of tissue exhibitingstructural information.

In another embodiment, global preoperative image data of tissue in ananatomical part is acquired using contrast based magnetic resonanceimaging and identifying. From the image data, a global vascularstructure within the tissue is identified. After exposing tissue duringa medical procedure in the anatomical part, intraoperative image data isacquired by scanning, using hyperspectral imaging, of a selected localregion of the tissue. From this intraoperative hyperspectral image data,a local vascular structure in the selected local region of the tissue islocated and identified. The global vascular image data is searched foridentifying and locating a portion of the global vascular structuregeometrically matching the local vascular structure. Upon identifyingand locating matching vascular structure between the two imagingmodalities, one or more local vascular structures in the selected localregion of the tissue is registered with the global vascular structurewithin the tissue for confirming location of the one or more localvasculature structures.

Thus, there is disclosed herein a computer implemented method ofintraoperatively confirming location of organized tissue structures inrelation to a patient's skeletal structure during a medical procedure,comprising:

acquiring preoperative image data of a patient's skeletal structure in avicinity of an anatomical part undergoing a medical procedure;

after exposing tissue during a medical procedure in the anatomical part,acquiring intraoperative image data by scanning a selected region oftissue, in a vicinity of the skeletal structure in the anatomical partundergoing the medical procedure using Polarization Sensitive-OpticalCoherence Tomography (PS-OCT);

identifying, from the intraoperative (PS-OCT) image data, regions oftissue exhibiting structural organization in the vicinity of theskeletal structure; and

using a priori known anatomical information about the regions of tissueexhibiting structural information for geometrically correlating andregistering the intraoperative (PS-OCT) image data with the preoperativeimage data of the skeletal structure in the vicinity of the anatomicalpart.

The pre-operative image data of the skeletal structure in a vicinity ofan anatomical part undergoing a medical procedure may be acquired usingany one of computed tomography (CT), magnetic resonance imaging (MRI)and optical coherence tomography (OCT).

An example of the MRI technique is T1 magnetic resonance imaging (T1MRI).

The tissue exhibiting structural organization includes, ligaments,tendons, muscle, cartilage, connective membranes, nerves, retina, bloodvessel walls, some bone structures, trachea, esophagus, tongue, teethand other connective tissues.

The a priori known anatomical information about the regions of tissueexhibiting structural information may include attachment points oftissue exhibiting structural information to the skeletal structurerelative to landmark positions on the skeletal structure.

Disclosed herein is a method, comprising the steps of:

a) intraoperatively confirming location of organized tissue structuresin relation to a patient's skeletal structure during a medicalprocedure, by:

-   -   acquiring preoperative image data of a patient's skeletal        structure in a vicinity of an anatomical part undergoing a        medical procedure;    -   after exposing tissue during a medical procedure in the        anatomical part, acquiring intraoperative image data by scanning        a selected region of tissue, in a vicinity of the skeletal        structure in the anatomical part undergoing the medical        procedure using Polarization Sensitive-Optical Coherence        Tomography (PS-OCT);    -   identifying, from the intraoperative (PS-OCT) image data,        regions of tissue exhibiting structural organization in the        vicinity of the skeletal structure; and    -   using a priori known anatomical information about the regions of        tissue exhibiting structural information for geometrically        correlating and registering the intraoperative (PS-OCT) image        data with the preoperative image data of the skeletal structure        in the vicinity of the anatomical part; and

b) using the registered intraoperative (PS-OCT) image data with thepreoperative image data of the skeletal structure in the vicinity of theanatomical part to plan a surgical trajectory to avoid selected regionsof the tissue exhibiting structural information.

Also disclosed is a computer implemented system for intraoperativelyconfirming location of organized tissue structures in relation to apatient's skeletal structure during a medical procedure, comprising:

a Polarization Sensitive-Optical Coherence Tomography (PS-OCT) apparatusconfigured to scan a selected region of tissue after the tissue isexposed during the medical procedure to acquire intraoperative imagedata of the selected region of tissue;

a computer processor having a memory storage, said PolarizationSensitive-Optical Coherence Tomography being connected to the computerprocessor, said memory storage having stored therein preoperative imagedata of a patient's skeletal structure in a vicinity of an anatomicalpart undergoing a medical procedure, said memory storage having storedtherein a priori known anatomical information about the regions oftissue exhibiting structural information;

said computer processor being programmed with instructions to

-   -   a) identify, from the intraoperative (PS-OCT) image data,        regions of tissue exhibiting structural organization in the        vicinity of the skeletal structure; and    -   b) use the stored priori known anatomical information about the        regions of tissue exhibiting structural information to        geometrically correlate and register the intraoperative (PS-OCT)        image data with the preoperative image data of the skeletal        structure in the vicinity of the anatomical part.

The present disclosure also provides a computer implemented method ofintraoperatively confirming location of vasculature structures locatedbelow a surface tissue during a medical procedure, comprising:

acquiring global preoperative image data of tissue in anatomical partundergoing a medical procedure using contrast based magnetic resonanceimaging and identifying, from the image data, a global vascularstructure within the tissue;

after exposing tissue during a medical procedure in the anatomical part,acquiring intraoperative image data by scanning, using hyperspectralimaging, a selected local region of the tissue in the anatomical partundergoing the medical procedure;

identifying, from the intraoperative hyperspectral image data, a localvascular structure in the selected local region of the tissue; andsearching the global vascular image data for identifying and locating aportion of the global vascular structure geometrically matching thelocal vascular structure, and upon identifying and locating matchingvascular structure, geometrically correlating and registering the localvascular structure in the selected local region of the tissue with the aglobal vascular structure within the tissue for confirming location ofthe local vasculature structures.

A method is disclosed, comprising the steps of:

acquiring global preoperative image data of tissue in anatomical partundergoing a medical procedure using contrast based magnetic resonanceimaging and identifying, from the image data, a global vascularstructure within the tissue;

after exposing tissue during a medical procedure in the anatomical part,acquiring intraoperative image data by scanning, using hyperspectralimaging, a selected local region of the tissue in the anatomical partundergoing the medical procedure;

identifying, from the intraoperative hyperspectral image data, a localvascular structure in the selected local region of the tissue;

searching the global vascular image data for identifying and locating aportion of the global vascular structure geometrically matching thelocal vascular structure, and upon identifying and locating matchingvascular structure, geometrically correlating and registering the localvascular structure in the selected local region of the tissue with the aglobal vascular structure within the tissue for confirming location ofthe local vasculature structures; and

b) using the registered hyperspectral image data with the preoperativeimage data of the vascular structure in the tissue of the anatomicalpart to plan a surgical trajectory to navigate through selected regionsof the tissue exhibiting vascular structure.

A further understanding of the functional and advantageous aspects ofthe disclosure can be realized by reference to the following detaileddescription and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments will now be described, by way of example only, withreference to the drawings, in which:

FIG. 1 shows an example navigation system to support minimally invasiveaccess port-based surgery.

FIG. 2 is block diagram illustrating system components of a navigationsystem.

FIG. 3 is a flow chart illustrating the processing steps involved in aport-based surgical procedure using a navigation system.

FIG. 4 is an example embodiment port based brain surgery using a videoscope.

FIG. 5A is an example embodiment of a video scope with camera couplerand illumination optics.

FIG. 5B is an example embodiment of a fiber bundle used to deliver lightfrom external light source to the video scope.

FIG. 5C is an example embodiment of a video scope and illuminationassembly.

FIG. 6 illustrates an example imaging optical sub-system of the videoscope.

FIG. 7 illustrates the arrangement of illumination optics and filterwheel for wide field of view arrangement.

FIG. 8A illustrates the non-uniform illumination obtained at the distalend of port with two illumination sources and a port with reflectivesurface.

FIG. 8B illustrates the near-uniform illumination obtained at the distalend of the port with two illumination sources and a port with roughsurface.

FIG. 9 an example embodiment illustrating a standard hyperspectralimaging system.

FIG. 10 is a flow chart illustrating a method to acquire hyperspectraldata and white-light images in a multiplex fashion.

FIG. 11 is an example embodiment illustrating imaging at specificwavelength bands.

FIG. 12 shows an example, non-limiting implementation of computercontrol system.

DETAILED DESCRIPTION

Various embodiments and aspects of the disclosure will be described withreference to details discussed below. The following description anddrawings are illustrative of the disclosure and are not to be construedas limiting the disclosure. Numerous specific details are described toprovide a thorough understanding of various embodiments of the presentdisclosure. However, in certain instances, well-known or conventionaldetails are not described in order to provide a concise discussion ofembodiments of the present disclosure.

As used herein, the terms, “comprises” and “comprising” are to beconstrued as being inclusive and open ended, and not exclusive.Specifically, when used in the specification and claims, the terms,“comprises” and “comprising” and variations thereof mean the specifiedfeatures, steps or components are included. These terms are not to beinterpreted to exclude the presence of other features, steps orcomponents.

As used herein, the term “exemplary” means “serving as an example,instance, or illustration,” and should not be construed as preferred oradvantageous over other configurations disclosed herein.

As used herein, the terms “about” and “approximately” are meant to covervariations that may exist in the upper and lower limits of the ranges ofvalues, such as variations in properties, parameters, and dimensions. Inone non-limiting example, the terms “about” and “approximately” meanplus or minus 10 percent or less.

Port-based surgery is a minimally invasive surgical technique where aport is introduced to access the surgical region of interest usingsurgical tools. Unlike other minimally invasive techniques, such aslaparoscopic techniques, the port diameter is larger than tool diameter.Hence, the tissue region of interest is visible through the port.Accordingly, exposed tissue in a region of interest at a depth fewcentimetres below the skin surface, and accessible through a narrowcorridor in the port, may be visualized using externally positionedoptical systems such as microscopes and video scopes.

Current methods of tissue differentiation during port-based surgicalprocedure involves visual verification using externally placed videoscope. Tissue differentiation may be useful because surgeons do not havea quantitative means of effectively confirming tissues types during asurgical procedure. Traditionally, hyperspectral imaging has not beenanticipated for intra-operative use in brain surgery because this methodhas a very limited depth of penetration in tissue and may not beeffectively used transcranially.

Further, the narrow corridor in port-based surgery is often occludedwhen a vessel is accidentally cut. In these incidents, the surgeon maybe required to stop his current surgical process (e.g. opening of dura,slight retraction of the sulcus for trans-sulcus navigation of port orresection of tumor tissue) and irrigate the cavity to get a better viewof the cavity. Further, such bleeding also limits the surgeon fromquickly identifying the location of bleeding so that the particularvessel wall can be coagulated to terminate bleeding.

Accordingly, in some aspects of the present disclosure, systems andmethods are provided for utilizing optical imaging in minimally invasiveport based surgical procedures. In some embodiments, hyperspectraldevices and methods are described for performing intraoperative tissuedifferentiation and analysis during such procedures.

FIG. 1 shows an example navigation system to support minimally invasiveaccess port-based surgery. FIG. 1 illustrates a perspective view of aminimally invasive port based surgical procedure. As shown in FIG. 1,surgeon 101 conducts a minimally invasive port-based surgery on apatient 102 in an operating room (OR) environment. A navigation system200 comprising an equipment tower, cameras, displays and trackedinstruments assist the surgeon 101 during his procedure. An operator 103is also present to operate, control and provide assistance for thenavigation system 200.

FIG. 2 is block diagram illustrating system components of an examplenavigation system. Navigation system 200 in FIG. 2 includes a monitor211 for displaying a video image, an equipment tower 201, a mechanicalarm 202, which supports an optical scope 204. Equipment tower 201 ismounted on a frame (i.e., a rack or cart) and may contain a computer,planning software, navigation software, a power supply and software tomanage the automated arm and tracked instruments. The example embodimentenvisions the equipment tower 201 as a single tower configuration withdual displays (211, 205), however, other configurations may also exists(i.e., dual tower, single display, etc.). Furthermore, equipment tower201 may also configured with a UPS (universal power supply) to providefor emergency power, in addition to a regular AC adapter power supply.

Example embodiment FIG. 2 also envisions equipment tower 201 havingrecording module 220 that provides real-time recording of the surgicalprocedure, capturing audio, video, sensory and multi-modal (i.e., CT,MR, US, etc) inputs from different sources. All relevant data isreceived at equipment tower 201 and stored in memory by recording module220. The surgical procedure may be automatically recorded at the outsetor be controlled by the operator and/or administrator. In otherembodiments, the procedure may be automatically recorded (by default),but there may be an option to override or delete the recording after theprocedure has been completed.

The patient's brain is held in place by a head holder 217 and insertedinto the head is an access port 206 and introducer 210. The introducer210 is tracked using a tracking system 213, which provides positioninformation for the navigation system 200. Tracking system 213 may be a3D optical tracking stereo camera similar to one made by NorthernDigital Imaging (NDI). Location data of the mechanical arm 202 and port206 may be determined by the tracking system 213 by detection offiducial markers 212 placed on these tools. A secondary display 205 mayprovide output of the tracking system 213. The output may be shown inaxial, sagittal and coronal views as part of a multi-view display.

Minimally invasive brain surgery using access ports is a recentlyconceived method of performing surgery on brain tumors previouslyconsidered inoperable. In order to introduce an access port into thebrain, an introducer 210 with an atraumatic tip may be positioned withinthe access port and employed to position the access portion within thehead. As noted above, the introducer 210 may include fiducial markers212 for tracking, as presented in FIG. 2. The fiducial markers 212 maybe reflective spheres in the case of optical tracking system or pick-upcoils in the case of electromagnetic tracking system. The fiducialmarkers 212 are detected by the tracking system 213 and their respectivepositions are inferred by the tracking software.

Once inserted into the brain, the introducer 210 may be removed to allowfor access to the tissue through the central opening of the access port.However, once introducer 210 is removed, the access port can no longerbe tracked. Accordingly, the access port may be indirectly tracked byadditional pointing tools configured for identification by thenavigation system 200.

In FIG. 2, a guide clamp 218 for holding the access port 206 may beprovided. Guide clamp 218 can optionally engage and disengage withaccess port 206 without needing to remove the access port from thepatient. In some embodiments, the access port can slide up and downwithin the clamp while in the closed position. A locking mechanism maybe attached to or integrated with the guide clamp, and can optionally beactuated with one hand, as described further below.

Referring again to FIG. 2, a small articulated arm 219 may be providedwith an attachment point to hold guide clamp 218. Articulated arm 219may have up to six degrees of freedom to position guide clamp 218.Articulated arm 219 may be attached or attachable to a point based onpatient head holder 217, or another suitable patient support, to ensurewhen locked in place, guide clamp 218 cannot move relative to thepatient's head. The interface between guide clamp 218 and articulatedarm 219 may be flexible, or optionally locked into place. Flexibility isdesired so the access port can be moved into various positions withinthe brain, but still rotate about a fixed point.

An example of such a linkage that can achieve this function is a slenderbar or rod. When the access port 206 is moved to various positions, thebar or rod will oppose such a bend, and move the access port 206 back tothe centered position. Furthermore, an optional collar may be attachedto the linkage between the articulated arm, and the access port guide,such that when engaged, the linkage becomes rigid. Currently, no suchmechanisms exist to enable positioning an access port in such a manner.

FIG. 3 is a flow chart illustrating the processing steps involved in aport-based surgical procedure using a navigation system. The first stepinvolves importing the port-based surgical plan (step 302). A detaileddescription of the process to create and select a surgical plan isoutlined in PCT Patent Application No. PCT/CA2014050272, titled“PLANNING, NAVIGATION AND SIMULATION SYSTEMS AND METHODS FOR MINIMALLYINVASIVE THERAPY”, which is hereby incorporated by reference in itsentirety, and which claims priority to U.S. Provisional PatentApplication Ser. Nos. 61/800,155 and 61/924,993, which are both herebyincorporated by reference in their entirety.

An example plan, as outlined above, may compose of pre-operative 3Dimaging data (i.e., MRI, ultrasound, etc.) and overlaying on it,received inputs (i.e., sulci entry points, target locations, surgicaloutcome criteria, additional 3D image data information) and displayingone or more trajectory paths based on the calculated score for aprojected surgical path. The aforementioned surgical plan may be oneexample; other surgical plans and/or methods may also be envisioned.

Once the plan has been imported into the navigation system (step 302),the patient is affixed into position using a head or body holdingmechanism. The head position is also confirmed with the patient planusing the navigation software (step 304).

Returning to FIG. 3, the next step is to initiate registration of thepatient (step 306). The phrase “registration” or “image registration”refers to the process of transforming different sets of data into onecoordinate system. Data may be multiple photographs, data from differentsensors, times, depths, or viewpoints. The process of “registration” isused in the present application for medical imaging in which images fromdifferent imaging modalities are co-registered. Registration isnecessary in order to be able to compare or integrate the data obtainedfrom these different modalities.

Those skilled in the art will appreciate that there are numerousregistration techniques available and one or more of them may be used inthe present application. Non-limiting examples include intensity-basedmethods which compare intensity patterns in images via correlationmetrics, while feature-based methods find correspondence between imagefeatures such as points, lines, and contours. Image registrationalgorithms may also be classified according to the transformation modelsthey use to relate the target image space to the reference image space.Another classification can be made between single-modality andmulti-modality methods. Single-modality methods typically registerimages in the same modality acquired by the same scanner/sensor type,for example, a series of MR images can be co-registered, whilemulti-modality registration methods are used to register images acquiredby different scanner/sensor types, for example in MRI and PET. In thepresent disclosure multi-modality registration methods are used inmedical imaging of the head/brain as images of a subject are frequentlyobtained from different scanners. Examples include registration of brainCT/MRI images or PET/CT images for tumor localization, registration ofcontrast-enhanced CT images against non-contrast-enhanced CT images, andregistration of ultrasound and CT.

Once registration is confirmed (step 308), the patient is draped (step310). Typically draping involves covering the patient and surroundingareas with a sterile barrier to create and maintain a sterile fieldduring the surgical procedure. The purpose of draping is to eliminatethe passage of microorganisms (i.e., bacteria) between non-sterile andsterile areas.

Upon completion of draping (step 310), the next steps is to confirmpatient engagement points (step 312) and then prep and plan craniotomy(step 314).

Upon completion of the prep and planning of the craniotomy step (step312), the next step is to cut craniotomy (step 314) where a bone flap istemporarily removed from the skull to access the brain (step 316).Registration data is updated with the navigation system at this point(step 322).

The next step is to confirm the engagement within craniotomy and themotion range (step 318). Once this data is confirmed, the procedureadvances to the next step of cutting the dura at the engagement pointsand identifying the sulcus (step 320). Registration data is also updatedwith the navigation system at this point (step 322).

In an embodiment, by focusing the camera's gaze on the surgical area ofinterest, this registration update can be manipulated to ensure the bestmatch for that region, while ignoring any non-uniform tissue deformationaffecting areas outside of the surgical field (of interest).Additionally, by matching overlay representations of tissue with anactual view of the tissue of interest, the particular tissuerepresentation can be matched to the video image, and thus tending toensure registration of the tissue of interest.

For example, video of post craniotomy brain (i.e. brain exposed) can bematched with an imaged sulcal map; the video position of exposed vesselscan be matched with image segmentation of vessels; the video position ofa lesion or tumor can be matched with image segmentation of tumor;and/or a video image from endoscopy within a nasal cavity can be matchedwith bone rendering of bone surface on nasal cavity for endonasalalignment.

In other embodiments, multiple cameras can be used and overlaid withtracked instrument(s) views, and thus allowing multiple views of thedata and overlays to be presented at the same time, which can tend toprovide even greater confidence in a registration, or correction in morethan dimensions/views.

Thereafter, the cannulation process is initiated (step 324). Cannulationinvolves inserting a port into the brain, typically along a sulci pathas identified in step 320, along a trajectory plan. Cannulation is aniterative process that involves repeating the steps of aligning the porton engagement and setting the planned trajectory (step 332) and thencannulating to the target depth (step 334) until the complete trajectoryplan is executed (step 324).

Returning to FIG. 3, the surgeon then performs resection (step 326) toremove part of the brain and/or tumor of interest. Resection (step 326)is a continual loop including both fine and gross resection (step 336).The next step involves hyperspectral imaging (step 338) which may beperformed on either fine or gross resection (step 336). Hyperspectralimaging (step 338) is used as a form of tissue differentiation and mayassist surgeons to investigate cancerous stem cells. Further, theability to hyperspectrally image tissue being operated on either as partof an external video scope or as a separate module may provide theability to perform chemical imaging using the absorption of tissue, theability to differentiate tissues based on scattering properties, and/orthe ability to improve visualization by imaging at wavelengths withreduced absorption or scattering properties.

Once resection is completed (step 326), the surgeon then decannulates(step 328) by removing the port and any tracking instruments from thebrain. Finally, the surgeon closes the dura and completes the craniotomy(step 330).

FIG. 4 illustrates an example port-based brain surgery procedure using avideo scope. In FIG. 4, operator 404, typically a surgeon, would alignvideo scope 402 to peer down port 406. Video scope 402 may be attachedto an adjustable mechanical arm 410. Port 406 may have a tracking tool408 attached to it where tracking tool 408 is tracked by a trackingsystem of a navigation system.

Even though the video scope 402 is commonly an endoscope or amicroscope, these devices introduce optical and ergonomic limitationswhen the surgical procedure is conducted over a confined space andconducted over a prolonged period such as the case with minimallyinvasive brain surgery.

FIG. 5A illustrates the design of a video scope that is composed of alens assembly 511 (explained later) and two illumination delivery points512. The lens assembly 511 is terminated at the eyepiece end with asealed window 501 at the proximal end. Sealed window 501 is typicallymade of quartz, to help maintain water seal since OR devices must besteam cleanable. The eyepiece end also has a camera coupler 505 thatprovides a standardized mounting point for a camera (not shown). Thecamera may be a standard definition (SD), high definition (HD) or ultrahigh definition (UHD) camera. In another embodiment, the camera may bereplaced by other imaging technologies such as Optical CoherenceTomography (OCT) or Polarization Sensitive-OCT. The distal end of thelens assembly is also sealed with a clear window 513 at the distal end.The distal end also supports illumination optics 512. In an alternateembodiment the distal end may be also optionally affixed with apolarizing filter to enable polarization sensitive imaging.

The PS OCT technique described herein may be used to specificallyvisualize tissue exhibiting structural organization. Examples of suchtissue structures include tendons that are attached to bones. Otherexamples of tissue that exhibit structural organization includeligaments, muscle, cartilage, tissue connective membrane, nerves,retina, blood vessel walls, some bone structures, trachea, esophagus,tongue and teeth. PS OCT commonly generates a heat map or pseudo coloredimage (reference: “Correlation of collagen organization withpolarization sensitive imaging of in vitro cartilage: implications forosteoarthritis,” W. Drexler et. al, The Journal of Rheumatology, Vol.28, No. 6, 1311-1318) where tissue structures with high degree oforganization appear highlighted. Hence the system can be used inorthopedic surgery to visualize tendons and optionally avoidunintentional damage to this tissue during a procedure. These identifiedregions of tissue exhibiting high level of structural organization (e.g.tendons and ligaments that are often located near skeletal structure)may be used in conjunction with a priori information, such as knownpoints of attachment of tendons to bones, to geometrically correlate PSOCT images to CT and MR images where bones are easily imaged.

The insertion sites, tendon-bone junctions and ligament-bone junctions,are known as entheses. The anatomical locations of entheses are wellknown and landmarks can be identified on the bone in the vicinity ofthese attachment points (reference: “Anatomy and biochemistry ofenthuses,” Michael Benjamin, Ann Rheum Dis 2000, Vol. 59, Issue 12, pg:995-999). Hence, this a priori anatomical information about the positionof the tendon or ligament relative to bone structures in the vicinitycan be used to register intraopertive PS-OCT image of the tendons orligaments with pre-operative images obtained using other modalities thataccurately image the bone structures.

For example the tendon-bone junction in the Achilles tendon enthesis isimmediately proximal to the superior tuberosity. This region ischaracterized by a highly irregular interface at the attachment pointsor junction. This characteristic structure of the bone can be used toidentify the junction where the tendon attaches to the bone. Thegeometric correlation of images that are thus obtained using differentmodalities, and often at different scales, is known as imageregistration or image fusion.

Common methods for multi-modal image registration mentioned aboveinclude those described in “Multi-modal image registration forpre-operative planning and image guided neurosurgical procedures,”Risholm, et. al, Neurosurg Clin N Am, 2011, April; 22(2): 197-206 and“Image registration of ex-vivo MRI to sparsely sectioned histology ofhippocampal and neocortical temporal lobe speciments,” Goubran et. al,Neurolmage, 83 (2013); 770-781. Broad classes of image registrationmethods for medical images is also described in detail in “A survey ofmedical image registration,” Maintz et. al, Medical Image Analysis(1998), Vol. 2, No. 1, pp: 1-36.

The illumination optics is comprised of fiber bundles 507 that arerotatably attached using a pair of connectors 510. The connectors 510allow the fiber bundles to rotate freely (570 in FIG. 5C) within theconnector while maintaining a fixed distance between the lens 509 andtip of the fiber bundle 507 using a loose sleeve 508. This rotationmovement will reduce the strain on the fiber bundle when the video scopeis moved on a holding system (not shown) or a mechanical arm 410 as seenin FIG. 4. The rotatable connector 510 also aid in easy cable managementwhen the mechanical arm 410 is moved during a surgical procedure. Theillumination optics are placed as close as possible to the objectivelens. One non-limiting example of spacing between the optics isapproximately 30 to 35 mm, or 32 to 34 mm, between the center of thelenses 509 where the diameter of lenses 509 is approximately 15 mm. Thisconfiguration is optimal for illuminating the bottom of a surgical portwith maximum intensity when the distal end of the video scope is between25 cm to 40 cm from the bottom of the surgical port. An opticalcompensator 503 is used to act as a thermal compensator to control thestress on optical components during steam cleaning. A holder 506provides an easy to grasp assembly to hold and manipulate the videoscope without introducing mechanical stress on the lens assembly. Thelens assembly is encased in a sealed barrel 511 to avoid ingression ofsteam and liquids during normal use and cleaning. The rotatableattachment mechanism 510 allows free rotation of the fiber bundles whenthe camera is moved manually or when mounted to a robotic positioningsystem. This, in turn, avoids undue stress on the fiber bundles that aresusceptible to fracture.

FIG. 5C illustrates a non-limiting example to realize a functionalitythat allows the illumination assembly 565 to rotate radially 560 aroundthe video scope barrel 502. The illumination assembly 565 is composed ofthe two fiber bundles 507 on either side of the video scope, mountingmechanism 508 and lens 509 (as in FIG. 5A). This allows the surgeon toadjust the radial orientation of the illumination and orient theillumination assembly so that it minimally obstructs the surgeon's viewof the surgical space. The illumination assembly can be freely rotatedwithout rotating the video scope by securing the video scope to anexternal positioning mechanism, such as 410, using a removable clamp 555and an associated lock 550. The removable clamp's distal end 555 and theassociated lock 550 may be mated together using a thread mechanism orany other mechanical fastening mechanism. The removal clamp's proximalend (not shown) may be secured to the external positioning mechanism410. It should be further noted that the rotation 560 enabled in thisdesign along with the rotation 570 of the fiber bundles within theconnectors enable positioning and orientation of the video scope withminimal interruption of the visible surgical space and minimize strainon the fiber bundles during motion. Finally, the illumination assembly565 may be replaced with alternative configurations such as ring lightsor single illumination points. Ring lights may be realized throughcircular arrangement of fiber strands (not shown) from an optical fiberbundle around the circumference of the objective lens. Singleillumination points may be realized through removal of one of the twosplit fiber bundles 507 from the design.

The illumination assembly preferably receives the light input from anoptical source that is located away from the video scope. This reducesthe total weight of the external scope and allows for easy manipulationof the video scope by a manual positioning system (not shown) or amechanical arm 410. The light from the light source is delivered to thevideo scope through the use of a fiber bundle. Presence of two deliverypoints represented by illumination optics 512 in FIG. 5A requires theuse of a fiber bundle that is split in two. This design of fiber bundleis also known as a Y-cables. An example embodiment of this Y-cabledesign is illustrated in FIG. 5B. In FIG. 5B, rotatable connections 508are provided on the fasteners 510 at the two distal end of the Y cable,providing a mechanism for freely rotating the fiber bundles to avoidfracture of the bundles. A strain-relief 527 helps maintain a minimumlimit on the bend radius 529 of the bundle between the two distal endsand the Y-junction 531. Y-junction 531 helps reduce bend strain on thefiber bundle 507. Strain-relief 533 similarly aids in reducing bendstrain near the connector 535 at the proximal end of the Y-cable. Crosssections 525 and 537 illustrate fiber bundles at the two ends of theY-cable. The length of the cable may be at least 40 cm with theY-junction 531 placed equidistant from the two ends. This dimensionprovides for placement of light source on a cart or instrumentationtower 201 sufficiently away from the mechanical arm 410 while minimizinglight loss due to excessive length of the fiber bundle.

FIG. 6 illustrates an optical design of the video scope that limits thediameter of the objective lens 600 (front lens). This design enables themounting of illumination optics immediately adjacent to the objectivelens so that the illumination beam can be almost collinear to the returnpath of the light reflected from the tissue. The illumination beam andthe reflected beam need to be as collinear as possible so that maximumillumination is delivered at the bottom of the access port 406. Finally,the optical design is constrained so that the length of the lensassembly is minimized to make the whole video scope 402 minimallyintrusive to the surgeon's field of view and facilitate easy access tothe surgical space by the surgeon. This constraint is a challenge inconventional optical design conventional optical design techniquesmaximize zoom by utilizing maximum available physical length of the lensassembly during the design process. This optical design of the presentdisclosure is adapted from a conventional endoscopic system thatconsists of objective lens 600, relay lens 602 and eyepiece 604. Thezoom parameter of the optical assembly is chosen such that the minimumfield of view (corresponding to maximum zoom) is equal to approximately13 mm. This dimension is the diameter of the surgical port. The field ofview of 13 mm needs to be achieved at a minimum working distance of 25cm where the minimum working distance is defined as the distance betweenthe distal end of the video scope (402 in FIG. 4) and bottom of thesurgical port (406 in FIG. 4). As explained in FIG. 5A, a coupler 505 isused to attach a camera at the eyepiece end (marked ‘E’ in FIG. 6). Theoptical design of the objective is composed of 1 doublet and 1 singlet;the relay is composed of 1 doublet and 1 singlet and the eyepiece iscomposed of 2 singlet and 1 doublet. Any manufacturing error iscompensated using one optical compensator 503 that is placed between theobjective and relay. The length of the optical sub-assembly is minimizedthrough the use of higher power lenses and fewer lens groups.

The type of surgical procedure determines either a wide-field of view(WFOV) or a narrow field of view (NFOV) video scope. For example, a necksurgery may benefit from a WFOV video scope where large area is capturedby the video scope; whereas, a port-based brain surgery may benefit froma NFOV video scope. Instead of attempting to address both these designrequirements using one device, two separate designs may be developedsuch that they share several sub-components and the manufacturingprocess. Hence, it is economical to manufacture two different designswhile sharing number of design elements and assembly procedure. BothWFOV and NFOV designs share a similar optical illumination system 512 asseen in FIG. 5A, The WFOV design can be realized by attaching a camerato the camera coupler 505. The zoom adjustment of the camera is used todetermine the field of view in this case.

FIG. 7 illustrates an assembly with a non-coaxial illumination source.The illumination system 710 is similar in design to that illustrated inFIG. 5A and consists of fiber bundles 704 (only a distal portion ofwhich are shown in the Figure). An air-filed opaque tube (also known asoptical tube) 702 is used to position the illumination mechanism awayfrom the camera attached to the coupler 505. It should be noted that anyrequired magnification may be provided by the camera lens (not shown buttypically attached to the camera coupler) for WFOV application. A finitespace that is at least 1 mm between the plane 706 of the distal end ofthe optical tube and the plane of the illumination optics 708 helpsisolate the illumination light from directly reaching the camera input.It should be further noted that the dimensions of the WFOV optics willbe such that the illumination will not be nearly coaxial with the pathof the reflected light. This is not a limitation in this configurationbecause WFOV is used to observe a surgical space that is larger that ofa port (which is approximately 13 mm). Hence, general illumination issufficient. Placement of the illumination source close to the cameradoes improve illumination of the surgical area compared to the use ofoverhead surgical lights and avoids glare from area outside of thesurgical space. The role of additional components, 712 and 714, areexplained below in the context of hyperspectral imaging.

In another embodiment of the video scope, the illumination sourcesplaced immediately adjacent to the distal end of the video scope may beemploy a light source such as luminance light emitting diodes or SuperLuminescent Diodes (SLD's) (not shown). Since the light sources are notcoaxial to the reflected light path (the light path incident on the lensand camera assembly), the light sources have to be aimed or steered atthe focal plane of interest. Such steering may be achieved using movablefiber bundle mounts 510 as shown in FIG. 5A.

Application of such externally positioned illumination sources inport-based imaging introduces several challenges. First, the walls ofthe port are either partially or fully reflective. This introduceslocalized regions in the imaged surface that have higher intensity ofincident light. Such regions are commonly known as hot-spots. It isdesirable to avoid such high intensity regions as these tend to saturatesensors and, hence, limit the dynamic range of the sensors in the cameramechanism. Use of post-processing to normalize intensities is lessoptimal as saturation of sensors results in information loss that cannotbe recovered. Presence of high intensity regions can be reduced throughthe use of surface textures on the port walls that diffuse the light.The impact of using smooth and rough surface texture on the port wallsis illustrated in FIGS. 8A and 8B, respectively. The reflectionsresulting from textured walls is referred to as Lambertian reflection.The assessment presented in FIGS. 8A and 8B were conducted usingray-tracing tools and the resulting intensity of light at the surface ofthe tissue (distal end of the port) were visualized using heat-maps orpseudo color where high intensity corresponded to white and lowintensity corresponded to black.

Another approach to uniformly illuminating at the bottom of the port isto model the light rays using a commonly known optical modelling method,such as ray tracing, and establish the optimal orientation of the lightsources that minimize hot-spots at the bottom of the surgical port.Orientation of the light sources may be modified using a beam steeringmechanism, such as the one illustrated in FIG. 5A. Alternatively, arobotic positioning system may be used to achieve this steering.

Port-based imaging is also limited by highly reflective nature of somebut not all regions of the brain tissue due to the presence of blood,CSF or other fluids. In the latter case, an initial image could beacquired to identify regions with high intensity reflected light andthis information can be used to reposition direction of the lightsources in an attempt uniformly distribute the incident light. Asdescribed above, imaging using white light has several challenges in theoperating room. Several of these challenges can be overcome by limitingthe spectral range of the light that is observed or by judiciouslycombining selected wavelength bands to visualize human tissue in theoperating room.

FIG. 9 illustrates a video scope that has been adapted to accommodatehyperspectral imaging capabilities. In this embodiment, tunable lightsource that is adapted based on the surgical context e.g. selection ofillumination spectral region where blood is highly absorptive (to detectblood clots) or transmissive (to avoid excessive light scattering) maybe used.

FIG. 9 illustrates one such system. The tunable light source is mainlycomposed of a broadband light source 1100, a spectral separationmechanism 1140, a spectral filtering mechanism 1150 and a mechanism tocombine the filtered frequency bands 1170. The combining mechanismconsists of a lens and a fiber bundle that mixes all the reflectedwavelength bands into one beam that is transmitted through the fiberbundle 507. The light from light source 1100 is passed through a slit1110 to generate a narrow beam. This light is then collimated usingoptical elements 1120 and 1130. The collimated beam is then split intoits spectral components using a prism (not shown), reflective ortransmission grating.

FIG. 9 illustrates the use of a reflective grating 1140. The spatiallyseparated beam is filtered by selectively reflecting portions of thespatially separated beam. This is achieved using a spatial lightmodulator, SLM 1150, such as a Digital Light Processor (TexasInstruments Inc). An SLM is composed of an array of micro-mirrors thatcan be electronically activated to act as mirrors or deactivated to actsas opaque surfaces. Hence, specific portions of the spectrum arereflected while other regions are suppressed based on the pattern ofactivated micro-mirrors. The beam that is now composed of selectiveportions of spectrum are combined using focusing optics 1160 and acombiner 1170.

The recombined beam is now composed of only those wavelengths that wereselectively reflected by the spatial light modulator, SLM 1150. Thislight can be used as the illumination source of an imaging system orexternal scope by transmitting the light via a light pipe 507 to theilluminator connector and lens mechanism 510 attached to the externalscope. It should be noted that the video scope illustrated in FIG. 9shows the connection of light pipe 507 to only one of the twoilluminator connectors 510 for the sake of simplicity of theillustration. Details of connecting the light pipe to the video scope isfurther explained in FIG. 5A.

The reflected light from the tissue 1198 is captured by the externalscope that is composed of lens assembly 502. As detailed in FIG. 5A, thelens assembly is composed; this light is captured using a highresolution detector 1125 that is usually a charge coupled device, CCD.The specific band of wavelengths that are reflected by the SLM arecontrolled by an SLM controller 1180 that is under the command of acomputer 1185. The same computer is used to acquire the image from thedetector 1125. Hence, the computer can synchronize the illumination of amaterial 1198 with a specific wavelength band or wavelength bands oflight and acquire corresponding reflected light. This association ofillumination wavelength and acquired image can be used to construct ahyper-spectral image where each image is a 2D or 1D image and the thirddimension is an index that corresponds to illumination wavelengthband(s). Since the individual micro-mirrors located in an SLM can beoperated at a rate as high as 4 kHz, subsequent frames of the field ofview can be obtained at different wavelength bands.

Further, some of the acquired frames can be for employed white-lightillumination of the tissue. This is possible by operating theacquisition camera at a frame rate that is sufficiently high to providesmooth video playback, as perceived by a human observer when white lightframes are intermittently obtained while collecting hyperspectral imageframes. For example, in some non-limiting examples, the frame rate maybe selected to be higher than 20 frames per second, higher than 24frames per second, or higher than 30 frames per second, in order tosupport white light video acquisition at such frame rates whileobtaining hyperspectral data. For example, at a camera frame rate higherthan 20 fps, a white-light image can be acquired every 1/20^(th) of asecond and any additional frame can be allocated for acquisition usingspecific wavelength bands. A white light video feed may then beseparately generated and displayed based on the collected white lightimages. This allows the surgeon to continuous view a white-light imageof the surgical area while acquiring any additional images at differentwavelength bands in a multiplexed manner. The white-light image stream(or video) may be viewed in one display or sub-section of a display andother images acquired using other wavelength bands may be viewed in asecond display or second sub-section of the same display.

The individual wavelength bands can be composed of non-overlappingindividual wavelength bands or combination of bands that may overlap.Alternatively, at least one of the acquired frame can correspond toillumination 1197 of the subject material 1198 using the entirewavelength band of the light source. The entire wavelength band could bealso normalized to ensure that all the intensity in the output lightemanating from the combiner 1170 is consistent across the entirespectrum. This is known as white balancing. In summary, the same opticalmechanism can be used to acquire hyperspectral images and white-lightimages that are interspersed among each other in the acquired sequenceof images. This embodiment eliminates the need for splitting theacquired beam into separate paths so that one beam is captured by ahyperspectral imaging system while the other beam is captured by awhite-light camera. This reduces the design complexity of the opticalsystem and aids in making the system more compact as the spectralshaping part of the system can be separated from the imaging systemusing a light pipe to channel the output light from the light source. Itshould be noted that the sample being imaged 1198 may be an ex-vivotissue sample or portion of the brain tissue that may be exposed througha port-based neurosurgical access inserted in the skull.

The software system used to acquire hyperspectral data and white-lightimages (or video) in a multiplex fashion is illustrated in FIG. 10.First the range of wavelengths (wave bands) that are of interest arestored in a table (step 1200). Then, specific wave band for illuminationis selected from the table (step 1220). Each entry in this table is usedto look up (step 1230) specific micro-mirrors that need to be activatedusing another table (step 1210). Hence, only the micro-mirrorsassociated with specific wavelength bands are activated (step 1240).Activation of a micro-mirror turns it into a micro-reflector instead ofan opaque surface. Hence, the sample 1198 in FIG. 9) is illuminated withlight (1197 in FIG. 9) that is composed of specific wavelength bands.The table (step 1200) may also include entries that activate the entirespatial light modulator (SLM). In this case, the SLM acts as a mirrorfor the entire bandwidth of the light source and the acquired image willcorrespond to white-light illumination.

Returning to FIG. 10, the reflected light from the illuminated sample isacquired (step 1250) by the same computer and associated with thespecific wavelength band (step 1260). The type of illumination(white-light versus specific wavelength band) used for each acquiredimage is interrogated (step 1270) in order to appropriately classify theacquired image as part of white-light image (video) or part of thehyperspectral image data set. If the acquired image corresponds to anarrow wavelength band then it is stored as part of the hyperspectralimage set (step 1280). If the image corresponds to white-lightillumination, it is stored as white-light image or a stream of suchimages may be captured to represent a video stream. This acquisition isrepeated (step 1215) until all the wavelength bands of interested aresequentially used to illuminate the sample material. Hence, theresulting image set will be composed of both hyperspectral image sets(step 1280) and white-light image sets (step 1290), all acquired usingthe same hardware.

Ideally, the video stream needs to be at least 30 frames per second toprovide a flicker-free video to the surgeon. If a total of 40 frames areacquired per second, the additional 10 frames may be used to storeimages corresponding to 10 distinct or overlapping wavelength bands.Hence, if the total frame rate of the acquisition system is n frames persecond, n−30 frames may be allocated towards n−30 wavelength bands inthe hyperspectral image data set.

An alternative to tunable light source 1110 shown in FIG. 9 may bemonochromatic, spanning ultra violet (UV), visible, and/or near infrared(NIR) wavelengths, continuous wave or pulsed that is used to illuminatethe tissue using free space or fiber coupled mechanism

In another embodiment, specific wavelength bands may be acquired byfiltering the reflected light from a broadband light source using suchspectral elements as discrete wavelength filters (on filter wheel orspatial on-chip filters), liquid crystal filters,spectrographs/spectrometers/spectral gratings, spatially varyinggratings, fiber-coupled spectrometers.

FIG. 7 also illustrates the implementation of discrete filters 712attached to a rotatable filter wheel 714) that may be motorized. Thisfilter mechanism is attached at the distal end of the video scope.Another alternative to discrete filters at the input to the video scopeis a liquid crystal-based tunable wavelength filter (not shown) to passonly a narrow range of wavelengths. This filter can be tuned to a numberof different wavelengths and operates in a similar manner to thediscrete filters as an image is acquired for each wavelength the filteris tuned to. In yet another embodiment, diffraction grating basedsystems that separate input light input its constituent wavelengths maybe used in lieu of the camera 1125 shown in FIG. 9. Imaging spectrometersystems rely on scanning the entrance slit of the system across thefield to be imaged. Thus the acquisition time is limited by the scanningtime. The entrance slit of the spectrometer can be either free space orfiber coupled to the optical path. If an array-to-line fiber mapping isutilized it is possible to acquire all spatial and spectral informationsimultaneously. The spectrometer could be alternatively equipped withSpatially Varying Gratings where a specialized diffraction grating thatallows for the collection of spectra from all pixels in a singleacquisition. The grating is divided into a number of spatial gratingseach with a varying direction of diffraction. An image is acquired thatcaptures the diffracted light from each of these grating regions, thisimage is then reconstructed to form the hyperspectral data set.

Non-limiting examples of camera 1125 include monochrome video camerawith resolution up to high definition (HD) or ultra high definition(UHD). CCD, CMOS, InGaAs, or HgCdTe device.

Another aspect of confocal hyperspectral imaging system is that theentire tissue surface does not have to be scanned in a raster pattern.Instead, random spots can be accumulated until a reasonable match isfound against pre-defined data classes. This can significantly reducethe data acquisition time associated with hyperspectral imaging.

In some embodiments, the hyperspectral imaging system illuminates thetissue with monochromatic or broadband light, collects light reflectedfrom the tissue, controls the wavelength of the detected light in such away that a series of images, each recorded at different wavelengths orwavelength ranges, is collected. This series of images, known as ahyperspectral dataset, is processed to extract tissue's bio-chemical ormicrostructural metrics and reduced to 2D (spatial). This reduced 2Dimage may be spatially registered and can be overlaid on the externalvideo scope image as well as any other pre- and intra-operative images.For example, methods of correlating image data are disclosed in PCTPatent Application No. PCT/CA2014/050269, titled “INTRAMODALSYNCHRONIZATION OF SURGICAL DATA” and filed on Mar. 14, 2014, the entirecontents of which are incorporated herein by reference for the purposesof the U.S. national phase patent application or continuation by passapplication that claims priority from this PCT application. Spatialregistration is realized by using navigation markers attached directlyon the camera or on structures rigidly and consistently attached to thecamera. This provides both location and orientation of the imagingsystem. This is further explained in the disclosure related to automatedguidance of imaging system.

The hyperspectral dataset 1280 in FIG. 10 is then processed to extractthe tissue specific information and reduce the dimensionality of thedata. Tissue specific information can range from tissue typeidentification to inferring pathology associated with a region of theacquired image. Examples of the possible processing methods includingthe following:

In one embodiment, if the spectral peaks or features of chemical(s) ofinterest are known, the spectra and be processed, through either peak orfeature detection algorithms, to detected the peaks or features to givean indication of the chemical presence and some indication of theconcentration or quality. This useful only if the specific chemicals ofinterest are known.

In one embodiment, the spectra of specific tissues or tissue states ofinterest can be acquired and stored in a database, as disclosed in PCTPatent Application No. PCT/CA2014/050269, titled “INTRAMODALSYNCHRONIZATION OF SURGICAL DATA” and filed on Mar. 14, 2014. Spectrathen acquired during the surgery can be compared to the spectra storedin the database for similarity and if sufficiently similar to give anindication of what tissue or tissue type the spectra was acquired from.

Multivariate/chemometric methods, which are a wide grouping ofstatistical techniques where a method is trained on spectra collectedfrom samples with known states (i.e., spectrum and correspondingchemical level, tissue type, tissue state, etc.), may be used to predictthe state of a new sample based on the acquired spectrum. Some of themore commonly used employed techniques include principal componentregression (PCR), partial least squares (PLS), and neural networks (NN).

The aforementioned analysis methods can be implemented in a computersystem, and hence the results of the analysis can be obtained innear-real time for appropriate use by a surgeon. This may significantlyreduce the need for similar analysis by a pathologist and reduces thewait time associated with obtaining results of such tissue analysis.Correlation metrics between newly acquired data and representative datain a knowledge-base (or database or training set) provide the surgeons ameans of quantifying tissue types. Such metrics may be a representationof confidence associated with automated inference provided by thesoftware algorithm.

Finally, the ability to selectively view narrow bands of the spectra orreject narrow bands of the spectra may allow the surgeon to rejectbright reflections from blood. Hence, the surgeon may be able to viewthe interior of the corridor and proceed with surgical resection oftumor even when the corridor is occluded by excessive bleeding. Thiswill reduce the need to constantly irrigate the narrow corridor andhence reduce interruption of the surgical procedure.

In another embodiment the optical characteristics and chemicalcomposition of blood may be taken advantage of to visualize vasculaturelocated at or immediately below tissue surface. For example, a commonchallenge associated with the dural opening step in cranial surgery isthe inability to anticipate the presence of vasculature immediatelybelow the dura. Hyperspectral imaging (HSI), with emphasis on red andnear infrared portions of the imaging spectrum, can be used toselectively visualize regions with high haemoglobin content. Due to theblood-brain barrier that naturally exists in the human brain, thistechnique will result in selective imaging of vasculature.

An example method for visualizing vascular structures located belowother tissue structures is disclosed in “Characterization of vascularstructures and skin bruises using hyperspectral imaging, image analysisand diffusion theory,” L. L. Randeberg et. al., Journal of Biophotonics,No. 1-2, 53-65 (2010). Another application of hyperspectral imaging,such as that enabled by invention presented in this document, is thereliance on reflectivity of hemoglobin that is particularly strong intumor microvasculature. This is described in detailed in “Hyperspectralimaging of hemoglobin saturation in tumor microvasculature and tumorhypoxia development,” B. S Sorg, et. al., Journal of Biomedical Optics,10(4), July/August 2005.

Similarly, OCT based imaging may be also used to visualize structureslocated immediately below the dura since the dura is not more than amillimetre thick. Vasculature is one of the predominant structureslocated below the dura. Others structures of relevance that can besimilarly imaged include the sulcal folds.

The vasculature that is visualized using the techniques described in thepreceding paragraphs is a map of the structure of the blood vessels inthe vicinity of the region being imaged. Such regions may include theregion in the vicinity of the trajectory along which a port is insertedin port-based cranial surgery. This vascular structure in the surgicalregion will be referred to as the in-situ vascular structure orintra-operative local vasculature. This in-situ geometry of the vascularstructure may be then be compared with whole-head vascular structureimages derived from MRI acquired after the injection of Gadolinium orother contrast medium in the veins. The latter whole-head images areobtained prior to a surgical procedure and referred to as pre-operativevascular structures. The pre-operatively vascular structures are imagedrelative to the anatomy of the patient. In other words, the location andorientation of this vascular structure is known relative to the anatomyof the patient.

This comparison of in-situ (intraoperative) vascular structure withpre-operative vascular structures may be used to infer the exactlocation of the in-situ vascular structures relative to thepre-operative vascular structures. This allows the surgeon to confirm orinfer their current surgical position relative to the anatomy of thepatient. Hence, the vascular structure can be used as a land-mark orreference frame for navigated surgical procedures. Although the aboveillustration is in the context of cranial surgery, it will beappreciated that the method can be extended to any other part of theanatomy where vasculature can be visualized pre-operatively andintra-operatively. Example procedures include, retinal surgery and lungbiopsy to mention just a few.

Geometric correlation of the local vascular structure with the globalvascular structure is feasible because the anatomy and pattern of bloodvessels is known (reference: “Cortical blood vessels of the humanbrain,” Duvernoy et. al., Brain Research Bulletin, Vol. 7, Issue 5,November 1981, pg 519-579 and “A computed tomographic guide to theidentification of cerebral vascular territories,” Damasio et. al., ArchNeurol, 1983; 40(3): 138-142. Thus while it is known that registration,in general, involves the geometric correlation of small scale image (or3D structure) with a large scale image (or 3D structure); however, thisgeometric correlation involves the use of features that are commonbetween the two image sets. The use of the vasculature by itself as afeature is as disclosed herein is the first instance of this. Thevasculature can be used as a feature because of its unique structure andthis uniqueness is well known (reference: see two papers cited in thisparagraph). Unique vascular structure is known to exist in severalregions of the body, for example the cerebral region, retina and thecardiac regions.

Thus, using the intraoperative hyperspectral image data, a localvascular structure in the selected local region of the tissue isidentified, and then the global vascular image data is searched foridentifying and locating a portion of the global vascular structuregeometrically matching the local vascular structure, and uponidentifying and locating matching vascular structure, geometricallycorrelating and registering the local vascular structure in the selectedlocal region of the tissue with the a global vascular structure withinthe tissue for confirming location of the local vasculature structures.The location, thus inferred, is invaluable for guiding tools in thelocal region for surgical procedures. Such surgical procedure is knownas navigated surgery.

It is noted that embodiments provided herein may employ software toprocess the 3D dimensional data sets to extract the information ofinterest, and to reduce the data to a 2D image that can be visualized inconjunction with or overlaid on the surgical image acquired by theexternal video scope. These software methods could include everythingfrom simple spectral peak detection to more sophisticated multivariate,chemometric, and data mining techniques to extract the metric ofinterest from the acquire spectra. The spectrum associated with eachpixel may be processed according to such methods.

As hyperspectral imaging is an optical technique and limited penetration(2-3 mm), its use is restricted to superficial tissues or those exposedthrough corridor surgery. The unique spectra of chemicals in tissueprovide the potential to use hyperspectral imaging to image chemicalcontent and from this provide useful qualitative or quantitativeinformation to the surgeon to assist in decision making during thesurgery. Chemical imaging can be used to differentiate between differenttissues based on differing chemical composition and associated differingabsorption (e.g., white vs grey matter), determine tissue state (e.g.,normal vs malignant), and determine tissue status and/or health (e.g.,state of oxygenation). The difference in spectral scattering propertiescan, similar to absorption changes, be used to determine the propertiesof tissue based on changes in cellular structure with tissue type (e.g.,fat vs nerve fiber) and state (e.g., changes in nuclear and overall cellsize with pre and cancerous states). Lastly, as the acquiredhyperspectral data set contains data acquired at a variety ofwavelength, images at only selected wavelengths or wavelength ranges toimprove the visualization of tissue (minima or maxima in absorption orscattering). For example, images at wavelengths where hemoglobinabsorption is at a minimum, the absorption due to blood will besignificantly reduced thus providing additional light for illumination.

This advantage of imaging at specific wavelength bands is illustrated inFIG. 11. FIG. 11 illustrates a standard color image (A) of a brainregion (Corpus Callosum) that is also captured using four differentwavelength bands centered at 400 nm (B), 500 nm (C), 600 nm (D) and 700nm (E) and a bandwidth of 10 nm each. It is evident that that 400 nmfilter band clearly illustrates tissue structures that are otherwiseinvisible in other wavelength bands.

FIG. 12 illustrates the key components of the computer system 1185 ofFIG. 9. FIG. 12 provides an example, non-limiting implementation ofcomputer control system 425, which includes one or more processors 430(for example, a CPU/microprocessor), bus 402, memory 435, which mayinclude random access memory (RAM) and/or read only memory (ROM), one ormore internal storage devices 440 (e.g. a hard disk drive, compact diskdrive or internal flash memory), a power supply 445, one morecommunications interfaces 450, and various input/output devices and/orinterfaces 460 such as a user interface for a clinician to providevarious inputs, run simulations etc.

Although only one of each component is illustrated in FIG. 12, anynumber of each component can be included computer control system 425.For example, a computer typically contains a number of different datastorage media. Furthermore, although bus 402 is depicted as a singleconnection between all of the components, it will be appreciated thatthe bus 402 may represent one or more circuits, devices or communicationchannels which link two or more of the components. For example, inpersonal computers, bus 402 often includes or is a motherboard.

In one embodiment, computer control system 425 may be, or include, ageneral purpose computer or any other hardware equivalents configuredfor operation in space. Computer control system 425 may also beimplemented as one or more physical devices that are coupled toprocessor 430 through one of more communications channels or interfaces.For example, computer control system 425 can be implemented usingapplication specific integrated circuits (ASIC). Alternatively, computercontrol system 425 can be implemented as a combination of hardware andsoftware, where the software is loaded into the processor from thememory or over a network connection.

In another example embodiment, a vertical slit or a focal point may beimaged by the video scope using a confocal optical design that iscommonly used in a microscope (not shown). The spot or slit may be thenimaged on a photomultiplier to generate a very sensitive hyper-spectralimaging system. The focal point may be swept across the sample surfaceusing a scanning mechanism. A commonly used scanning mechanism is agalvanometer mirror system.

The specific embodiments described above have been shown by way ofexample, and it should be understood that these embodiments may besusceptible to various modifications and alternative forms. It should befurther understood that the claims are not intended to be limited to theparticular forms disclosed, but rather to cover all modifications,equivalents, and alternatives falling within the spirit and scope ofthis disclosure.

While the Applicant's teachings described herein are in conjunction withvarious embodiments for illustrative purposes, it is not intended thatthe applicant's teachings be limited to such embodiments. On thecontrary, the applicant's teachings described and illustrated hereinencompass various alternatives, modifications, and equivalents, withoutdeparting from the embodiments, the general scope of which is defined inthe appended claims.

1. A computer implemented method of intraoperatively confirming locationof organized tissue structures in relation to a patient's skeletalstructure, comprising: acquiring preoperative image data of a patient'sskeletal structure in a vicinity of an anatomical part; after exposingtissue during a medical procedure in the anatomical part, acquiringintraoperative image data by scanning a selected region of tissue, in avicinity of the skeletal structure in the anatomical part undergoing themedical procedure using Polarization Sensitive-Optical CoherenceTomography (PS-OCT); identifying, from the intraoperative (PS-OCT) imagedata, regions of tissue exhibiting structural organization in thevicinity of the skeletal structure; and using a priori known anatomicalinformation about the regions of tissue exhibiting structuralinformation for geometrically correlating and registering theintraoperative (PS-OCT) image data with the preoperative image data ofthe skeletal structure in the vicinity of the anatomical part.
 2. Themethod according to claim 1, wherein the pre-operative image data of theskeletal structure in a vicinity of an anatomical part is acquired usingany one of computed tomography (CT), magnetic resonance imaging (MRI)and optical coherence tomography (OCT).
 3. The method according to claim2, wherein the magnetic resonance imaging is T1 magnetic resonanceimaging (T1 MRI).
 4. The method according to claim 1, wherein the tissueexhibiting structural organization includes, ligaments, tendons, muscle,cartilage, connective membranes, nerves, retina, blood vessel walls,some bone structures, trachea, esophagus, tongue, teeth and otherconnective tissues.
 5. The method according to claim 1, wherein the apriori known anatomical information about the regions of tissueexhibiting structural information include attachment points of tissueexhibiting structural information to the skeletal structure relative tolandmark positions on the skeletal structure.
 6. A method, comprisingthe steps of: a) intraoperatively confirming location of organizedtissue structures in relation to a patient's skeletal structure during amedical procedure, by: acquiring preoperative image data of a patient'sskeletal structure in a vicinity of an anatomical part undergoing amedical procedure; after exposing tissue during a medical procedure inthe anatomical part, acquiring intraoperative image data by scanning aselected region of tissue, in a vicinity of the skeletal structure inthe anatomical part undergoing the medical procedure using PolarizationSensitive-Optical Coherence Tomography (PS-OCT); identifying, from theintraoperative (PS-OCT) image data, regions of tissue exhibitingstructural organization in the vicinity of the skeletal structure; andusing a priori known anatomical information about the regions of tissuebiting structural information for geometrically correlating andregistering the intraoperative (PS-OCT) image data with the preoperativeimage data of the skeletal structure in the vicinity of the anatomicalpart; and b) using the registered intraoperative (PS-OCT) image datawith the preoperative image data of the skeletal structure in thevicinity of the anatomical part to plan a surgical trajectory to avoidselected regions of the tissue exhibiting structural information.
 7. Themethod according to claim 6, wherein the pre-operative image data of theskeletal structure in a vicinity of an anatomical part undergoing amedical procedure is acquired using any one of computed tomography (ct),magnetic resonance imaging (MRI) and optical coherence tomography (OCT).8. The method according to claim 7, wherein the magnetic resonanceimaging is T1 magnetic resonance imaging (T1 MRI).
 9. The methodaccording to claim 6, wherein the tissue exhibiting structuralorganization includes, ligaments, tendons, muscle, cartilage, connectivemembranes, nerves, retina, blood vessel walls, some bone structures,trachea, esophagus, tongue, teeth and other connective tissues.
 10. Themethod according to claim 6, wherein the a priori known anatomicalinformation about the regions of tissue exhibiting structuralinformation include attachment points of tissue exhibiting structuralinformation to the skeletal structure relative to landmark positions onthe skeletal structure.
 11. A computer implemented system forintraoperatively confirming location of organized tissue structures inrelation to a patient's skeletal structure, comprising: a PolarizationSensitive-Optical Coherence Tomography (PS-OCT) apparatus configured toscan a selected region of tissue to acquire intraoperative image data ofthe selected region of tissue; a computer processor having a memorystorage, said Polarization Sensitive-Optical Coherence Tomography beingconnected to the computer processor, said memory storage having storedtherein preoperative image data of a patient's skeletal structure in avicinity of an anatomical part, said memory storage having storedtherein a priori known anatomical information about the regions oftissue exhibiting structural information; said computer processor beingprogrammed with instructions to a) identify, from the intraoperative(PS-OCT) image data, regions of tissue exhibiting structuralorganization in the vicinity of the skeletal structure; and b) use thestored priori known anatomical information about the regions of tissueexhibiting structural information to geometrically correlate andregister the intraoperative (PS-OCT) image data with the preoperativeimage data of the skeletal structure in the vicinity of the anatomicalpart.
 12. A computer implemented method of intraoperatively confirminglocation of vasculature structures located below a surface tissue duringa medical procedure, comprising: acquiring global preoperative imagedata of tissue in anatomical part undergoing a medical procedure usingcontrast based magnetic resonance imaging and identifying, from theimage data, a global vascular structure within the tissue; afterexposing tissue during a medical procedure in the anatomical part,acquiring intraoperative image data by scanning, using hyperspectralimaging, a selected local region of the tissue in the anatomical partundergoing the medical procedure; identifying, from the intraoperativehyperspectral image data, a local vascular structure in the selectedlocal region of the tissue; and searching the global vascular image datafor identifying and locating a portion of the global vascular structuregeometrically matching the local vascular structure, and uponidentifying and locating matching vascular structure, geometricallycorrelating and registering the local vascular structure in the selectedlocal region of the tissue with the a global vascular structure withinthe tissue for confirming location of the local vasculature structures.13. The method according to claim 12 wherein the contrast agent is aGadolinium contrast agent.
 14. A method, comprising the steps of:acquiring global preoperative image data of tissue in an anatomical partundergoing a medical procedure using contrast based magnetic resonanceimaging and identifying, from the image data, a global vascularstructure within the tissue; after exposing tissue during a medicalprocedure in the anatomical part, acquiring intraoperative image data byscanning, using hyperspectral imaging, a selected local region of thetissue in the anatomical part undergoing the medical procedure;identifying, from the intraoperative hyperspectral image data, a localvascular structure in the selected local region of the tissue; searchingthe global vascular image data for identifying and locating a portion ofthe global vascular structure geometrically matching the local vascularstructure, and upon identifying and locating matching vascularstructure, geometrically correlating and registering the local vascularstructure in the selected local region of the tissue with the a globalvascular structure within the tissue for confirming location of thelocal vasculature structures; and b) using the registered hyperspectralimage data with the preoperative image data of the vascular structure inthe tissue of the anatomical part to plan a surgical trajectory tonavigate through selected regions of the tissue exhibiting vascularstructure.
 15. The method according to claim 14 wherein the contrastagent is a Gadolinium contrast agent.
 16. A computer implemented methodof intraoperatively confirming location of vasculature structureslocated below a surface tissue during a medical procedure, comprising:hyperspectral imaging apparatus configured to scan a selected region oftissue below a surface of the tissue after the tissue is exposed duringthe medical procedure to acquire intraoperative image data of vascularstructure in the selected region of tissue; a computer processor havinga memory storage, said hyperspectral imaging apparatus being connectedto the computer processor, said memory storage having stored thereinpreoperative image data of tissue in anatomical part undergoing amedical procedure acquired using contrast based magnetic resonanceimaging, said image data containing a global vascular structure withinthe tissue; said computer processor being programmed with instructionsto a) identify, from the intraoperative hyperspectral image data, one ormore local regions of tissue exhibiting vascular structure; and b)search the global vascular image data to identify and locate one or moreportions of the global vascular structure that geometrically matches theone or more local vascular structures, and upon identifying and locatingone or more matching vascular structures, geometrically correlate andregister the one or more local vascular structures in the selected localregion of the tissue with corresponding regions of the global vascularstructure within the tissue for confirming location of the one or morelocal vasculature structures.
 17. The system according to claim 11,wherein the preoperative image data of the skeletal structure in thevicinity of an anatomical part is acquired using any one of computedtomography (CT), magnetic resonance imaging (MRI) and optical coherencetomography (OCT).
 18. The system according to claim 17, wherein themagnetic resonance imaging is T1 magnetic resonance imaging (T1 MRI).19. The system according to claim 11, wherein the tissue exhibitingstructural organization includes, ligaments, tendons, muscle, cartilage,connective membranes, nerves, retina, blood vessel walls, some bonestructures, trachea, esophagus, tongue, teeth and other connectivetissues.
 20. The system according to claim 11, wherein the a prioriknown anatomical information about the regions of tissue exhibitingstructural information include attachment points of tissue exhibitingstructural information to the skeletal structure relative to landmarkpositions on the skeletal structure.